Work

Chinese Grammatical Correction Using BERT-based Pre-trained Model

Year: 2020

Type: preprint

Abstract: In recent years, pre-trained models have been extensively studied, and several downstream tasks have benefited from their utilization. In this study, we verify the effectiveness of two methods that incorporate a BERT-based pre-trained model developed by Cui et al. (2020) into an encoder-decoder model on Chinese grammatical error correction tasks. We also analyze the error type and conclude that sentence-level errors are yet to be addressed.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2011.02093

Authors: Wang, Hongfei, Kurosawa, Michiki, Katsumata, Satoru, Komachi, Mamoru

Institution: Tokyo Metropolitan University

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Japan Society for the Promotion of Science

Awards: Compositionality and Interpretation of Word Embeddings, Acquisition and Analysis of Distributed Representations of Words and Sentences Focusing on Language Learners' Errors

OpenAlex ID: W3095033764

Cites: 19

Cited by: 4

Related to: 10